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Dr. Barrios-Faúndez, Tomás
Nombre de publicación
Dr. Barrios-Faúndez, Tomás
Nombre completo
Barrios Faúndez, Tomás Patricio
Facultad
Email
tomas@ucsc.cl
ORCID
3 results
Research Outputs
Now showing 1 - 3 of 3
- PublicationNew a posteriori error estimator for an stabilized mixed method applied to incompressible fluid flows(Applied Mathematics and Computation, 2019)
; ; González, MaríaWe consider an augmented mixed finite element method for incompressible fluid flows and develop a simple a posteriori error analysis. We obtain an a posteriori error estimator that is reliable and locally efficient. We provide numerical experiments that illustrate the performance of the corresponding adaptive algorithm and support its use in practice. - PublicationA posteriori error analysis of an augmented mixed finite element method for Darcy flowWe develop an a posteriori error analysis of residual type of a stabilized mixed finite element method for Darcy flow. The stabilized formulation is obtained by adding to the standard dual-mixed approach suitable residual type terms arising from Darcy’s law and the mass conservation equation. We derive sufficient conditions on the stabilization parameters that guarantee that the augmented variational formulation and the corresponding Galerkin scheme are well-posed. Then, we obtain a simple a posteriori error estimator and prove that it is reliable and locally efficient. Finally, we provide several numerical experiments that illustrate the theoretical results and support the use of the corresponding adaptive algorithm in practice
- PublicationLow cost a posteriori error estimators for an augmented mixed FEM in linear elasticityWe consider an augmented mixed finite element method applied to the linear elasticity problem and derive a posteriori error estimators that are simpler and easier to implement than the ones available in the literature. In the case of homogeneous Dirichlet boundary conditions, the new a posteriori error estimator is reliable and locally efficient, whereas for non-homogeneous Dirichlet boundary conditions, we derive an a posteriori error estimator that is reliable and satisfies a quasi-efficiency bound. Numerical experiments illustrate the performance of the corresponding adaptive algorithms and support the theoretical results.